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Pyupgrade to Python 3.9 (#4718)

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* Pyupgrade to Python 3.9

* updating DIRECTORY.md

Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
This commit is contained in:
Christian Clauss
2021-09-07 13:37:03 +02:00
committed by GitHub
parent 5d5831bdd0
commit cecf43d648
142 changed files with 523 additions and 530 deletions
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12
data_structures/heap/heap.py
View File

@ -1,4 +1,6 @@
from typing import Iterable, List, Optional
from __future__ import annotations
from typing import Iterable
class Heap:
@ -25,19 +27,19 @@ class Heap:
"""
def __init__(self) -> None:
self.h: List[float] = []
self.h: list[float] = []
self.heap_size: int = 0
def __repr__(self) -> str:
return str(self.h)
def parent_index(self, child_idx: int) -> Optional[int]:
def parent_index(self, child_idx: int) -> int | None:
"""return the parent index of given child"""
if child_idx > 0:
return (child_idx - 1) // 2
return None
def left_child_idx(self, parent_idx: int) -> Optional[int]:
def left_child_idx(self, parent_idx: int) -> int | None:
"""
return the left child index if the left child exists.
if not, return None.
@ -47,7 +49,7 @@ class Heap:
return left_child_index
return None
def right_child_idx(self, parent_idx: int) -> Optional[int]:
def right_child_idx(self, parent_idx: int) -> int | None:
"""
return the right child index if the right child exists.
if not, return None.

16
data_structures/heap/randomized_heap.py
View File

@ -3,7 +3,7 @@
from __future__ import annotations
import random
from typing import Generic, Iterable, List, Optional, TypeVar
from typing import Generic, Iterable, TypeVar
T = TypeVar("T")
@ -16,8 +16,8 @@ class RandomizedHeapNode(Generic[T]):
def __init__(self, value: T) -> None:
self._value: T = value
self.left: Optional[RandomizedHeapNode[T]] = None
self.right: Optional[RandomizedHeapNode[T]] = None
self.left: RandomizedHeapNode[T] | None = None
self.right: RandomizedHeapNode[T] | None = None
@property
def value(self) -> T:
@ -26,8 +26,8 @@ class RandomizedHeapNode(Generic[T]):
@staticmethod
def merge(
root1: Optional[RandomizedHeapNode[T]], root2: Optional[RandomizedHeapNode[T]]
) -> Optional[RandomizedHeapNode[T]]:
root1: RandomizedHeapNode[T] | None, root2: RandomizedHeapNode[T] | None
) -> RandomizedHeapNode[T] | None:
"""Merge 2 nodes together."""
if not root1:
return root2
@ -69,13 +69,13 @@ class RandomizedHeap(Generic[T]):
[-1, 0, 1]
"""
def __init__(self, data: Optional[Iterable[T]] = ()) -> None:
def __init__(self, data: Iterable[T] | None = ()) -> None:
"""
>>> rh = RandomizedHeap([3, 1, 3, 7])
>>> rh.to_sorted_list()
[1, 3, 3, 7]
"""
self._root: Optional[RandomizedHeapNode[T]] = None
self._root: RandomizedHeapNode[T] | None = None
for item in data:
self.insert(item)
@ -151,7 +151,7 @@ class RandomizedHeap(Generic[T]):
"""
self._root = None
def to_sorted_list(self) -> List[T]:
def to_sorted_list(self) -> list[T]:
"""
Returns sorted list containing all the values in the heap.

14
data_structures/heap/skew_heap.py
View File

@ -2,7 +2,7 @@
from __future__ import annotations
from typing import Generic, Iterable, Iterator, Optional, TypeVar
from typing import Generic, Iterable, Iterator, TypeVar
T = TypeVar("T")
@ -15,8 +15,8 @@ class SkewNode(Generic[T]):
def __init__(self, value: T) -> None:
self._value: T = value
self.left: Optional[SkewNode[T]] = None
self.right: Optional[SkewNode[T]] = None
self.left: SkewNode[T] | None = None
self.right: SkewNode[T] | None = None
@property
def value(self) -> T:
@ -25,8 +25,8 @@ class SkewNode(Generic[T]):
@staticmethod
def merge(
root1: Optional[SkewNode[T]], root2: Optional[SkewNode[T]]
) -> Optional[SkewNode[T]]:
root1: SkewNode[T] | None, root2: SkewNode[T] | None
) -> SkewNode[T] | None:
"""Merge 2 nodes together."""
if not root1:
return root2
@ -69,13 +69,13 @@ class SkewHeap(Generic[T]):
[-1, 0, 1]
"""
def __init__(self, data: Optional[Iterable[T]] = ()) -> None:
def __init__(self, data: Iterable[T] | None = ()) -> None:
"""
>>> sh = SkewHeap([3, 1, 3, 7])
>>> list(sh)
[1, 3, 3, 7]
"""
self._root: Optional[SkewNode[T]] = None
self._root: SkewNode[T] | None = None
for item in data:
self.insert(item)